Upsets make March Madness special. 

In 2018, Virginia was the top overall seed heading into the tournament. They got shocked by UMBC, as a 16 seed beat a 1 seed for the first time in men’s NCAA tournament history.

The only thing better than watching these upsets is picking them in your bracket. How can we use analytics to do that?

Maybe others have some insight. For the past two seasons, The Athletic has written about Bracket Breakers, a math model that predicts March Madness upsets.

Let’s focus on one result: teams that pull off the upset tend to shoot a lot of threes. This makes sense, as shooting more threes should increase the variance in points. An increased variance favors the underdog.

Last year, I decided to test this and other hypotheses about upsets. However, I didn’t restrict myself to tournament games like the Bracket Breakers model. 

Instead, I considered all college basketball games in which a team closed in the markets as an underdog of six or more points but won outright. As a data scientist, I like a larger sample size.

In the 2021-22 season, college basketball teams took 37% of their field goal attempts from three. Underdogs of six or more points that won had a three point rate 1.7% lower. Pulling off the upset is not about shooting more threes.

In addition, I’ve found no statistical relationship between a team’s three point rate and variance in points per possession. The idea that shooting more threes increases variance is not supported by the data.

Then what leads to upsets? Making three pointers.

During the 2021-22 season, underdogs of six or more points that won made 5.5% more of their threes than their season average. Favorites that lost made 5.5% less from behind the arc.

This difference in three point shooting from both teams resulted in a seven point swing. This was by far the largest effect that I found.

For example, there is also an effect from two point field goals. Like from behind the arc, underdogs make a higher rate of two pointers while favorites make a lower rate. This resulted in a two point benefit for the underdog.

Fantastic. Three point shooting leads to upsets. All we need to do is predict three point field goal percentage.

However, this is difficult. In a landmark study called The 3-point line is a lottery, Ken Pomeroy found no correlation in a team’s three point percentage from early to late season. This was true for both offense and defense.

The results on offense should be particularly surprising. Shooting is a skill, right? How can it not be predictive?

That’s a nuanced question for another day. For March Madness, let’s conclude that the randomness of three point shooting makes it difficult to predict upsets.

Except for one team. I’ll get into that team that bucks three point regression next week.

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Gonzaga is not the same team as the past two seasons. Star players like Chet Holmgren and Jalen Suggs left as NBA lottery picks, and Gonzaga even lost at home to Loyola Marymount.

One look at the numbers points out the weakness: defense. By my adjusted points per possession, Gonzaga ranks 74th after top 10 campaigns the past two seasons.

Perhaps Gonzaga will get better at defense in the tournament. This crop of youngsters can’t find the effort every possession, but maybe the increased intensity in the Big Dance will lead to better defense.

To study this, let’s look at how my metrics have predicted past tournament performance. Based on points per possession in the regular season, I calculate an offensive and defense rating for each team.

From these metrics, I make a prediction for points per possession in tournament games. Let’s compare these predictions to the actual efficiencies in tournament games. 

At first, I looked at the last four tournaments and found that the average prediction was off by less than one point in 100 possessions each year. This is a good sign that my algorithms work.

To determine whether poor defensive teams played better in the tournament, I looked at these predictions in games with a defense that ranked worse than 25th. 

Here are the results by tournament year, and a negative number implies the defense did better than expected.

• 2022, -0.06
• 2021, -1.73
• 2019, 1.55
• 2018, -3.50

This is promising, as overall these poor defenses get a point per 100 possessions better in the tournament over these four tournaments. About 60% of defenses met the criteria of being outside the top 25 in my defensive metrics.

The problem is that the answer changes over a longer time span. When I look at the past eight tournaments, these poor defensive teams gave up 1.28 points per 100 possessions more, not less, than expected. These results come from the prior years.

• 2017, 5.17
• 2016, 1.93
• 2015, 1.71
• 2014, 5.21

In each of these tournaments, poor defenses gave up significantly more points per possession than expected based on pre-tourney metrics. A part of this increase might come from increased fouling at the end of games, as teams get more desperate in elimination games. 

This study gives no clear signal that a poor defense will improve in the tournament. 

This is not a good omen for Gonzaga. This team struggles to defend the dribble drive and switch on the pick and roll. Not to pick on any one player, but offensive star Drew Timme either lacks the physical ability or effort to play good defense.

However, Gonzaga is the best offensive team in the nation by my adjusted points per possession. Could they make a deep run by out-scoring other teams? They did in a 100-90 win over Alabama earlier this season.

The offensive wizardry makes Gonzaga a fun team to watch in 2023. But despite their performance against St. Mary’s in the West Coast Conference tournament final, don’t expect the defense to get better.

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This post was sent to The Power Rank’s email newsletter. This is a free service that strives to be:

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You’ll also get my March Madness cheat sheet that makes it drop dead easy to fill out your bracket. And you’re going to need analytics more than ever in 2023 with such parity in college basketball.

In addition, you get a free pdf of my book How to Win Your NCAA Tournament Pool.

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You want to win your March Madness pool, and analytics is going to lead the way. However, analytics is not the only thing you need.  

In fact, if you get this other thing wrong, analytics will not help. Unless you’re Biff from Back to the Future Part II, you might as well light your entry fee on fire.

To understand the one thing you must get right to win your March Madness pool, consider an analogy.

Steph Curry walks into a gym. There are a bunch of college players looking to get into the NBA. Steph is feeling generous, so he sets up a contest. Beat Steph in a three point shooting contest, get an NBA rookie contract.

As the greatest shooter to ever grace a basketball court, Steph goes out and sinks 17 of 25 three point shots, an amazing mark. Can any college kid beat him?

You might think Steph will certainly win the contest. However, it depends on the numbers of college kids in the shooting contest.

For every college player that steps up, let’s assume a 95% chance that he makes fewer shots than Steph. If two players enter the contest, the chance that Steph beats both is 0.95 times 0.95. He still has a healthy 90% chance to win the contest.

However, Steph’s odds to win decrease with every additional contestant, as his win probability gets another multiplicative factor of 0.95. If 13 college players participate, the odds are about 50-50 that Steph wins. This goes down to 7.6% with 50 college players.

If you use analytics to enter your March Madness pool, you’re like Steph in this shooting contest. You have great odds to beat any one person.

However, your odds go down with more people in your pool. The bigger the pool, the more likely someone gets lucky and beats you.

Someone like Grandma. She doesn’t know anything about college basketball. However, she’s Catholic, and that matters in 2018.

Grandma has Villanova, the oldest Catholic university in Pennsylvania, as champion. In addition, she’s also friends with Sister Jean and picks Loyola of Chicago to make the Final Four. 

When Loyola of Chicago made the Final Four, Grandma got points that no one else gets from the South Region. When Villanova beats Michigan in the finals, Grandma wins her pool. It’s as if Shaq beats Steph Curry in a three point shooting contest.

Here’s the take home message: Do not get in a large pool. For a contest with a single winner, the pool must be less than 100 people. Maximize your odds of winning by getting in a pool of 10 or less.

Get your March Madness cheat sheet

These nuggets were sent to The Power Rank’s email newsletter. This is a free service that strives to be:

• Valuable
• Concise
• Entertaining

You’ll also get my March Madness cheat sheet that makes it drop dead easy to fill out your bracket. And you’re going to need analytics more than ever in 2023 with such parity in college basketball.

In addition, you get a free pdf of my book How to Win Your NCAA Tournament Pool.

To get this free service delivered straight into your inbox, enter your best email address and click on “Sign up now!”